Narratives and opinion polarization: a survey experiment.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
26 08 2024
26 08 2024
Historique:
received:
15
12
2023
accepted:
12
08
2024
medline:
26
8
2024
pubmed:
26
8
2024
entrez:
25
8
2024
Statut:
epublish
Résumé
We explore the impact of narratives on beliefs and policy opinions through a survey experiment that exposes US subjects to two media-based explanations of the causes of COVID-19. The Lab Narrative ascribes the pandemic to human error and scientific misconduct in a Chinese lab, and the Nature Narrative describes the natural causes of the virus. First, we find that both narratives influence individual beliefs about COVID-19 origins. More precisely, individual beliefs tend to be swayed in the direction of the version of the facts to which one is more exposed generating a potential source of polarization by exposure. Second, only the Nature Narrative unidirectionally affects policy opinions by increasing people's preferences toward climate protection and trust in science, therefore representing a channel for one-sided polarization by exposure. Finally, we also explore the existence of heterogeneous effects of our narratives, finding that the Lab Narrative leads to opinion polarization between Republican- and Democratic-leaning states on climate change and foreign trade. This indicates the existence of an additional channel that can lead policy opinions to diverge, which we denote polarization by social context.
Identifiants
pubmed: 39183317
doi: 10.1038/s41598-024-70012-6
pii: 10.1038/s41598-024-70012-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
19732Informations de copyright
© 2024. The Author(s).
Références
Brunnermeier, M. K., James, H. & Landau, J.-P. The Euro and the battle of ideas (Princeton University Press, Princeton, NJ, 2018).
Gentzkow, M., Shapiro, J. M. & Taddy, M. Measuring group differences in high-dimensional choices: Method and application to congressional speech. Econometrica 87, 1307–1340 (2019).
doi: 10.3982/ECTA16566
Shiller, R. J. Narrative economics: How stories go viral and drive major economic events (Princeton University Press, Princeton, 2019).
doi: 10.1515/9780691189970
Roos, M. & Reccius, M. Narratives in economics. J. Econ. Surveys (2021).
Eliaz, K. & Spiegler, R. A model of competing narratives. Am. Econ. Rev. 110, 3786–3816 (2020).
doi: 10.1257/aer.20191099
Media bias and voting. Della Vigna, S. & Kaplan, E. The Fox News effect. Quart. J. Econ. 122, 1187–1234 (2007).
Bakshy, E., Messing, S. & Adamic, L. A. Exposure to ideologically diverse news and opinion on facebook. Science 348, 1130–1132 (2015).
doi: 10.1126/science.aaa1160
pubmed: 25953820
Levy, R. Social media, news consumption, and polarization: Evidence from a field experiment. Am. Econ. Rev. 111, 831–70 (2021).
doi: 10.1257/aer.20191777
Krupka, E. & Weber, R. A. The focusing and informational effects of norms on pro-social behavior. J. Econ. Psychol. 30, 307–320 (2009).
doi: 10.1016/j.joep.2008.11.005
Silver, L., Devlin, K. & Huang, C. Unfavorable views of China reach historic highs in many countries. Pew Res. Center6 (2020).
Tollefson, J. How Trump damaged science-and why it could take decades to recover. Nature 586, 190–194 (2020).
doi: 10.1038/d41586-020-02800-9
pubmed: 33020603
Kwa, K. X. Experiments and qualitative methods: towards a methodological framework. Res. Handbook Motivat. Public Admin. 105–120 (2022).
Kaufmann, E. Can narratives of white identity reduce opposition to immigration and support for hard Brexit? A survey experiment. Polit. Stud. 67, 31–46 (2019).
doi: 10.1177/0032321717740489
Cattaneo, C. & Grieco, D. Turning opposition into support to immigration: The role of narratives. J. Econ. Behav. Organ. 190, 785–801 (2021).
doi: 10.1016/j.jebo.2021.08.015
Bolsen, T. & Shapiro, M. A. The US news media, polarization on climate change, and pathways to effective communication. Environ. Commun. 12, 149–163 (2018).
doi: 10.1080/17524032.2017.1397039
Gehring, K. & Grigoletto, M. Analyzing climate change policy narratives with the character-role narrative framework. CESifo Working Paper10429 (2023).
Balafoutas, L., Libman, A., Selamis, V. & Vollan, B. Exposure to conspiracy theories in the lab. Econ. Polit. Stud. 9, 90–112 (2021).
doi: 10.1080/20954816.2020.1818930
Brader, T., Valentino, N. A. & Suhay, E. What triggers public opposition to immigration? Anxiety, group cues, and immigration threat. Am. J. Polit. Sci. 52, 959–978 (2008).
doi: 10.1111/j.1540-5907.2008.00353.x
Gadarian, S. K. & Albertson, B. Anxiety, immigration, and the search for information. Polit. Psychol. 35, 133–164 (2014).
doi: 10.1111/pops.12034
Hyde, M. The Guardian, http://theguardian.com/world/2021/jan/28/white-house-great-concern-over-covid-origin-misinformation-from-within-china , Accessed on January 29, 2021.(2021)
Hrynowski, Z. Several issues tie as most important in 2020 election. Retrieved from Gallup website: www.news.gallup.com/poll/276932/several-issues-tie-important-2020-election.aspx (2020).
Stevens, L. & Ron-Levey, I. Trust in science essential in battle against COVID-19. Gallup Blog (2020).
Tversky, A. & Kahneman, D. Choices, values, and frames (Cambridge University Press, 2000).
Brañas-Garza, P. Promoting helping behavior with framing in dictator games. J. Econ. Psychol. 28, 477–486 (2007).
doi: 10.1016/j.joep.2006.10.001
Thaler, R. H. Behavioral economics: Past, present, and future. Am. Econ. Rev. 106, 1577–1600 (2016).
doi: 10.1257/aer.106.7.1577
Tversky, A. & Kahneman, D. Availability: a heuristic for judging frequency and probability. Cogn. Psychol. 5, 207–232 (1973).
doi: 10.1016/0010-0285(73)90033-9
DeMarzo, P. M., Vayanos, D. & Zwiebel, J. Persuasion bias, social influence, and unidimensional opinions. Quart. J. Econ. 118, 909–968 (2003).
doi: 10.1162/00335530360698469
Crawford, V. P. & Sobel, J. Strategic information transmission. Econometrica 50, 1431–1451 (1982).
Kamenica, E. & Gentzkow, M. Bayesian persuasion. Am. Econ. Rev. 101, 2590–2615 (2011).
Ottaviani, M. & Sørensen, P. N. Reputational cheap talk. Rand J. Econ. 37, 155–175 (2006).
Pavesi, F. & Scotti, M. Good lies. Eur. Econ. Rev. 141, 103965 (2022).
McFadden, D. et al. Quantal choice analysis: A survey. Ann. Econ. Soc. Meas. 5, 363–390 (1976).
Andrews, K. T. & Caren, N. Making the news: Movement organizations, media attention, and the public agenda. Am. Sociol. Rev. 75, 841–866 (2010).
doi: 10.1177/0003122410386689
Makowsky, M. D. Religion, clubs, and emergent social divides. J. Econ. Behavior Organ. 80, 74–87 (2011).
doi: 10.1016/j.jebo.2011.02.012
Abramowitz, A. I. & Saunders, K. L. Is polarization a myth?. J. Polit. 70, 542–555 (2008).
doi: 10.1017/S0022381608080493
Glaeser, E. L. & Ward, B. A. Myths and realities of American political geography. J. Econ. Perspect. 20, 119–144 (2006).
doi: 10.1257/jep.20.2.119
Harrington, J. R., Gelfand, J. & Michele,. Tightness–looseness across the 50 united states. Proc. Natl. Acad. Sci. 111, 7990–7995 (2014).
doi: 10.1073/pnas.1317937111
pubmed: 24843116
pmcid: 4050535
Murphy, K. M. & Shleifer, A. Persuasion in politics. Am. Econ. Rev. 94, 435–439 (2004).
doi: 10.1257/0002828041301687
Glaeser, E. L., Ponzetto, G. A. & Shapiro, J. M. Strategic extremism: Why Republicans and Democrats divide on religious values. Quart. J. Econ. 120, 1283–1330 (2005).
doi: 10.1162/003355305775097533
Momsen, K. & Ohndorf, M. Information avoidance, selective exposure, and fake (?) news: Theory and experimental evidence on green consumption. J. Econ. Psychol. 88, 102457 (2022).
doi: 10.1016/j.joep.2021.102457
Wodtke, G. T. & Zhou, X. Effect decomposition in the presence of treatment-induced confounding: A regression-with-residuals approach. Epidemiology 31, 369–375 (2020).
doi: 10.1097/EDE.0000000000001168
pubmed: 32251064
Chen, Y. & Yang, D. Y. The impact of media censorship: 1984 or brave new world?. American Economic Review 109, 2294–2332 (2019).
doi: 10.1257/aer.20171765
Allcott, H., Braghieri, L., Eichmeyer, S. & Gentzkow, M. The welfare effects of social media. Am. Econ. Rev. 110, 629–76 (2020).
doi: 10.1257/aer.20190658
Bail, C. A. et al. Exposure to opposing views on social media can increase political polarization. Proc. Natl. Acad. Sci. 115, 9216–9221 (2018).
doi: 10.1073/pnas.1804840115
pubmed: 30154168
pmcid: 6140520
Joyella, M. Fox News dominates May ratings, but CNN prime time jumps 117%. Forbes (2020).
Iyengar, S. & Hahn, K. S. Red media, blue media: Evidence of ideological selectivity in media use. J. Commun. 59, 19–39 (2009).
doi: 10.1111/j.1460-2466.2008.01402.x
Schroeder, E. & Stone, D. F. Fox News and political knowledge. J. Public Econ. 126, 52–63 (2015).
doi: 10.1016/j.jpubeco.2015.03.009
Garrett, G. The post-covid-19 world will be less global and less urban. Knowledge@Wharton, www-knowledge. wharton. upenn. edu/article/post-covid-19-world-will-less-global-less-urban (2020).
IPSOS, M. O. R. I. Coronavirus: Opinion and reaction. Results from a multi-country poll. Ipsos (2020).
Saad, L. Americans as concerned as ever about global warming (News, Gallup, 2019).
Gray, E. & Jackson, C. Two thirds of citizens around the world agree climate change is as serious a crisis as coronavirus. Ipsos (2020).
Hepburn, C., O’Callaghan, B., Stern, N., Stiglitz, J. & Zenghelis, D. Will COVID-19 fiscal recovery packages accelerate or retard progress on climate change?. Oxf. Rev. Econ. Policy 36, S359–S381 (2020).
doi: 10.1093/oxrep/graa015
Mendiluce, M. & Siri, J. The covid-19 recovery can be the vaccine for climate change. In World Economic Forum (2020).
AAAS. Perceptions of science in America. A report from the public face of science initiatives (American Academy of Arts & Sciences: Cambridge, MA, 2018).
Palan, S., Schitter, C. & Prolific,. ac–A subject pool for online experiments. J. Behav. Exp. Financ. 17, 22–27 (2018).
doi: 10.1016/j.jbef.2017.12.004
Jones, J. Democratic states exceed republican states by four in 2018. Gallup22 (2019).
Gimpel, J. G. & Karnes, K. A. The rural side of the urban-rural gap. PS Polit. Sci. Politics 39, 467–472 (2006).
doi: 10.1017/S1049096506060859
Karadja, M., Mollerstrom, J. & Seim, D. Richer (and holier) than thou? The effect of relative income improvements on demand for redistribution. Rev. Econ. Stat. 99, 201–212 (2017).
doi: 10.1162/REST_a_00623
Bansak, K. Estimating causal moderation effects with randomized treatments and non-randomized moderators. J. R. Stat. Soc. Ser. A Stat. Soc. 184, 65–86 (2021).
doi: 10.1111/rssa.12614
Deaton, A. & Stone, A. Do context effects limit the usefulness of self-reported wellbeing measures. Research Program in Development Studies Working Paper 288 (2013).